The solution would be to accept that the classification algorithm was too error probe to be usable for non-toy applications.

We are going in circles. An error rate of 2% (heck! 20%!) would not make a classification unusable, that was what one of the grandfather posts was arguing.

https://adssettings.google.com/u/0/authenticated

Here Google can infer my gender and my age and personal interests just from my search history. I am sure this is not perfect either, it is still immensely useful for advertising.

Not the best example, given google lets you toggle your ad segments when they get them wrong and isn't baisising that guess based on physical presentation; the ad segment "male" is just a comment on the things you search and click on.

Why are you imposing the error tolerances the user should have? Shouldn't that be their choice?

If someone wants to build and train their own model that assigns a binary gender based on pictures that's their own choice, and because of that freedom they can't force google to do it for them.

Right, it's just that usually the concept with goods and services is that you're paying someone else to do it for you because you either can't or don't want to.

If I'm the author of the tool, I can impose whatever I want, no? It's not like people have a God-given right to have Google tag photos with genders for them.

So the best argument to do is the fact that you have a legal right to?

The argument in this case is that the potential for misuse outweighs the potential benefits.